AgentUX-4B

3

—

by

yasserrmd

Language Model

OTHER

4B params

New

3 downloads

Early-stage

Try on Hugging Face Add to Compare

Edge AI:

Mobile

Laptop

Server

9GB+ RAM

Mobile

Laptop

Server

Quick Summary

AgentUX‑4B is a compact, agentic reasoning model designed for UI layout generation, component reasoning, and lightweight code structuring tasks.

Device Compatibility

Mobile

4-6GB RAM

Laptop

16GB RAM

Server

GPU

Minimum Recommended

4GB+ RAM

Training Data Analysis

🔵 Good (6.0/10)

Researched training datasets used by AgentUX-4B with quality assessment

Specialized For

general

multilingual

Training Datasets (1)

🔵 6/10

general

multilingual

Key Strengths

•Scale and Accessibility: 750GB of publicly available, filtered text
•Systematic Filtering: Documented heuristics enable reproducibility
•Language Diversity: Despite English-only, captures diverse writing styles

Considerations

•English-Only: Limits multilingual applications
•Filtering Limitations: Offensive content and low-quality text remain despite filtering

Explore our comprehensive training dataset analysis

View All Datasets

Code Examples

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

🔧 Usage Examplepythontransformers

from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline

model_id = "yasserrmd/AgentUX-4B"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True)

pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)

prompt = "Create a responsive layout with sidebar and header using Flexbox."
response = pipe(prompt, max_new_tokens=512)[0]["generated_text"]
print(response)

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